One large insurance risk company is betting that the computing power of a private cloud can better help estimate losses from terror attacks and extreme weather.

When terrorist attacks, natural disasters, or extreme weather events occur, first responders quickly arrive to the scene. Right behind them, it seems, are the insurance companies. In order to process claims, these companies are relying on exceedingly complicated software packages. But as the software begins moving to the cloud, victims of disaster will also see their claims more rapidly settled. RMS, a California-based risk management firm, just launched a new software package last month which uses massive amounts of computing power to predict financial loss from terrorism or hurricanes before it happens.

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The platform and proprietary cloud service, called RMS(One), is designed for underwriters to quickly make data-intensive calculations such as damage if a bomb goes off in front of a particular building entrance or a tornado takes a path that intersects with a particular commercial area. Rather than offering insurance themselves, RMS develops the models used to estimate the potential financial losses from a particular event. This information is then used by insurers and reinsurers to offer policies, process claims, and then make contingency plans.

“Our clients’ use cases are computationally demanding,” CEO Hemant Shah says. “Historically, they’ve tended to manage risk through the rearview mirror. By the time they gather, analyze, and interpret data, there’s a lot of lag in the system. Model-based analytics are very computationally demanding, and often clients make decisions about risk with weeks, months, and days of lag. We are transitioning that into a real-time environment so if a global insurer wants to make a decision, it can make those analytics in real time and power underwriters to make more efficient decisions.”

A recent white paper published by RMS detailed some specifics of their models for terror attacks, which are plugged into simulations of over 90,000 possible large-scale attacks against 9,800 different targets worldwide with 35 potential methods of attack. Depending on whether the attack occurs with a car bomb, a truck bomb, or a chemical weapon, entirely different damage happens to nearby individuals, buildings, and property. The company’s other core competency, models for extreme weather events, are similarly complicated.

Building a cloud-based analytics platform for these sorts of predictions also poses unique challenges to RMS and competitors like XtremeGIS. Shah notes that many of his customers have sensitive security needs, and that insurers and reinsurers as a whole belong to a conservative industry with specific privacy and security requirements. This has led to certain safeguards like the construction of a top-down private cloud rather than a preexisting infrastructure such as AWS.

With catastrophic events, both man-made and natural, increasingly common, the ability for insurers to move quickly and deftly has the potential to ease the painful process victims have to go through to file claims.